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IFRS 9: Implementing a robust infrastructure for the new accounting regime

April 25, 2016 – By Shlomo Cohen, Risk SME, AxiomSL

International Financial Reporting Standard 9 (IFRS 9) is a true game-changer for accounting. Having historically been required to analyze the past performance of financial instruments in their accounts, firms will now need to take a forward-looking approach to accounting. This change has wide-ranging operational and technical implications. With implementation set for 1 January 2018, now is the time for firms to ensure their infrastructure is ready for a new era of accounting.

IFRS 9 is the International Accounting Standards Board’s (IASB) response to the weaknesses of the incumbent International Accounting Standard 39 (IAS 39), which failed to account properly for the risks that were ignited by the financial crisis of 2007-8. To avoid a repeat of this situation, IFRS 9 requires firms to model future events in the macroeconomic environment and calculate expected credit losses (ECL) for their financial instruments over either a 12-month or lifetime period. They will then need to offset these expected losses with capital provisions.

In order to accurately anticipate future events and the impact they will have on their credit exposures, firms will need not only financial data, which has long been the staple of accounting, but also risk data. Combining financial and risk data is without doubt one of the most significant challenges presented by IFRS 9.

Integrating risk and financial data

Finance and risk typically operate in isolation from one another and, over the years, have developed very different cultures. Finance must produce highly accurate and auditable figures which, among other things, inform investors about the performance of a firm. As a result, finance is defined by many detailed rules, and accounts are produced in a highly structured and controlled environment. Risk, on the other hand, must be able to respond quickly in fast-changing situations. As a result, risk is based on principles rather than hard-and-fast rules.

These two very different cultures mean that financial and risk data is organized differently and is therefore very difficult to combine, as required by IFRS 9. The best way for firms to overcome this challenge is by using a single calculation and reporting platform, which can provide both the structured production environment required by finance, and the flexibility required by risk. The platform should not impose constraints on the location of the data or require duplication or double storage. It should be possible for both IT and business users to understand the logic that is being used. Data lineage information will also be important for establishing trust in the platform.

Data ownership

IFRS 9 also raises important questions about the ownership of risk data. Chief risk officers (CROs) need this data not only to run their internal risk assessments, but also to comply with a growing list of regulatory requirements, such as Basel lll, the Basel Committee on Banking Supervision’s 239 (BCBS 239) Principles for Effective Risk Data Aggregation and Risk Reporting and, in Europe, for the Asset Quality Review (AQR) and European Banking Authority’s (EBA) stress tests. However, the introduction of IFRS 9 means chief financial officers (CFOs) will also need this risk data to fulfill their accounting requirements. There are a number of ways firms can address these competing claims for ownership of risk data:

by giving ownership of risk data to the CRO

by giving ownership of risk data to the CFO

by giving the CRO and CFO shared ownership of the risk data

by producing duplicate sets of risk data

Data volumes

The data challenges introduced by IFRS 9 do not stop with the combination of risk and financial data. Assessing ECL under the IFRS 9 framework means calculating impairments for all assets in the ‘amortized cost’ or ‘fair value through other comprehensive income’ categories. As a result, the number of assets to be impaired will increase dramatically from thousands under IAS 39 to millions under IFRS 9. Firms will therefore need to integrate much larger volumes of granular data than ever before. And the requirement for impairments to be calculated on a point-in-time (PIT) basis means this data will also need to be updated far more frequently than before.

Finally, in order to model future market events as part of IFRS 9, firms will need external data, such as macroeconomic information. This is a big change, as firms have historically relied on internal financial data to run their accounting processes. They must now consider how they are going to source large volumes of external economic and market data (both qualitative and quantitative data) and store it for future analysis.

In order to address the above challenges, firms will need to significantly change their internal databases. For example, they will need to automate and streamline the processes of extracting, transferring, validating and enriching the necessary data. The best way to do this is by using a single, flexible calculation and reporting platform, which allows them to manage data at different levels of granularity and also allows them to tailor the frequency at which data is updated based on the needs of different lines of business.

The roll-out of IFRS 9 is a watershed moment in the development of accounting practices. By thinking strategically about all of the changes that are required and by focusing on the various data challenges, firms can adapt smoothly and efficiently to the new regime.